Wireless data communication networks today typically involve data transmission of modulated information signals from one or more network controller devices to one or more wireless client devices, and back, over various types of wireless communications links. In order to maximize the amount of information transferred in the presence of signal fading and signal interference, most modern wireless communications networks employ multiple levels of modulation as well as multiple coding rates that are dynamically selected based on the levels of signal fading or signal interference.
Typical modulation schemes include Binary Phase Shift Keying (BPSK, having 1 bit/symbol), Quadrature Phase Shift Keying (QPSK, having 2 bits/symbol), and Quadrature Amplitude Modulation (e.g., 16-QAM, 64-QAM, etc., having 4 bits/symbol, 6 bits/symbol, etc.). These modulation schemes may be assigned to data communications between individual client devices and network controller devices (e.g., network cell basestations). As would be understood by those skilled in the art, the higher a modulation order the more data that can be carried over a communications link (measured in terms of bits/data symbol or bits per second).
As communication link bandwidth largely depends on symbol rate and not bit rate, it is advantageous to increase the bit rate per symbol, when feasible, to increase channel throughput. Typically, this can be accomplished by implementing a higher order of modulation (e.g., switching from BPSK to 16-QAM) for each symbol. However, for each additional bit encoded in a data symbol, the symbol states become less distinct from each other. This can make it more difficult, if not impossible, for a receiver to detect a symbol correctly, particularly in the presence of signal interference.
A Signal to Interference plus Noise Ratio (SINR) is the ratio of the received strength of a desired signal (e.g., a directed basestation pilot signal) to the received strength of undesired signals such as noise and interference. Generally, the better the SINR, the higher the modulation order that can be employed and that greater the throughput that can be achieved over a particular network communications link. Accordingly, within most modern data communications networks, there exist multiple SINR thresholds between which only specific modulation levels can be efficiently employed. Further, in order to achieve a more stable throughput under particular SINR scenarios it is important for data communications systems to employ multiple coding rates. Predesignated coding rates offer a desired level of system redundancy (e.g., error correction and stability) for each level of modulation implemented over a network communications link.
As one example, a network controller may assign a portion of client devices operating in close vicinity to a network basestation to transmit and receive data using a 64-QAM modulation level. To ensure a desired level of redundancy (e.g., in the presence of interference) the network controller may designate the 64-QAM modulation to be encoded at a half rate (i.e., 64-QAM 1/2), resulting in a throughput of 3 bits/symbol with an acceptably low bit error rate instead of a throughput of 6 bits/symbol with an unacceptably high bit error rate. The employment of error correction coding ensures that the communicating portion of client devices will receive a desired quality of service (QOS) in accordance with the half rate coding scheme. QOS metrics affected by interference or signal fading may include, but are not limited to, communications quality, queuing delay, information loss, dropping existing network sessions, blocking new network sessions, etc.
In general, the closer a client device is to a network basestation within a coverage area, the better the SINR the client device will achieve. This is because the client device generally receives a stronger signal with less interference the closer it is to the base station. In contrast, the closer a client device is to an edge of a coverage area or the further away a client device is from the nearest network basestation, the weaker a signal and greater the level of interference the client device will receive and the worse the SINR the client device will achieve.
Typically, when end users subscribe to a data communications service on a wireless data communication network (e.g., packet-switched networks), they enter into a service agreement with a network service provider which specifies the QOS that they will achieve on the network. One of the most crucial parameters of a QOS agreement is the data throughput a client device should achieve. In theory, it would be most beneficial to a client if their achievable throughput were independent of the type or level of MCS employed. Unfortunately, this is not always possible or even desirable, because when a client device is using a lower order MCS, they consume much more communication link bandwidth than when they are using a higher order MCS.
For example, the transfer of a data packet using BPSK (1 bit/symbol) requires six times the amount of bandwidth that the transfer the same data packet requires when using 64-QAM (6 bits/symbol). When network bandwidth is limited or when congestion occurs on the link, it is not always optimal to limit throughput to clients already using the least amount of bandwidth (e.g., clients using 64-QAM modulation) so that clients already consuming the most bandwidth (e.g., clients using BPSK modulation) can achieve a slightly higher throughput.
If a network controller device, having a packet data scheduler, provided for an equal-throughput scenario amongst all client devices in a network cell, the collective throughput of the system would be lower than a network controller device, having a packet data scheduler that provided for an equal-bandwidth scenario amongst all client devices in a network cell. However, under an equal-bandwidth scenario, users of lower order MCS may receive a disproportionately low throughput compared with users of higher order MCS.
By way of example, Table 1 illustrates various modulation distributions that could be seen on a particular wireless network under both an equal-throughput and an equal-bandwidth scheduling scenario for the same set of network devices. This example presumes a network coverage area of fixed size having a large population of client devices distributed in a uniformly random fashion.
TABLE 1ChannelChannelPercentage of CPEmodulationmodulationon channel usingdistribution:distribution:Modulation andModulation andEqual-BandwidthEqual-ThroughputCoding Schemecoding schemeSchedulingSchedulingQPSK-1/2 x60.96%0.96%9.5%QPSK-1/2 x42.82%2.82%18.6% QPSK-1/2 x24.78%4.78%15.7% QPSK 1/27.15%7.15%11.8% QPSK 3/47.78%7.78%8.5%16-QAM 1/213.01% 13.01% 10.7% 16-QAM 3/415.98% 15.98% 8.8%64-QAM 2/37.63%7.63%3.1%64-QAM 3/47.01%7.01%2.6%64-QAM 5/632.88% 32.88% 10.8% 
The percentage of CPE using each modulation and coding scheme is shown in the second column of Table 1. In the equal-bandwidth scheduling scenario of Table 1, the modulation distribution on the channel is the same as the modulation distribution of all the distributed client devices. For example, 32.88% of the client devices use a 64-QAM 5/6 MCS, so 32.88% of the channel bandwidth is consumed by the 64-QAM 5/6 users. At the other end of the scale, only 0.96% of the users require QPSK-1/2×6 MCS (QPSK-1/2 with a repetition factor of 6, equivalent to an overall MCS of QPSK-1/12), and therefore only 0.96% of the channel bandwidth is consumed by those users.
In the equal-throughput scheduling scenario of Table 1, the scheduler assigns equal-throughput to all distributed client devices on the channel. However, the MCS distribution seen on the channel is significantly different than the distribution of MCS amongst the client devices. For example, even though only 0.96% of the client devices use a QPSK-1/2×6 MCS, they are consuming 9.5% of the channel bandwidth. The client devices using a 64-QAM 5/6 MCS utilize the channel more efficiently, but they only receive 10.8% of the channel bandwidth. Considering at least the above tradeoffs, neither an equal-throughput nor an equal-bandwidth scheduling scenario offers an ideal, flexible solution to real-world data rate scheduling problems experienced by most network service providers.
Therefore, there continues to be a need for improved data communications systems and methods that employ hybrid modulation and coding scheme (MCS) throughput assignments to communications channels within a data communications network. It would be beneficial if these hybrid scheduling schemes offered real-world solutions that would benefit the collective users of a particular network data communications channel. It would also be beneficial if these improved systems and methods provided for easy modification of the hybrid scheduling schemes in accordance with a particular service provider's QOS objectives.